This e-Research adaptive user interface (eRaUI) project is aiming at developing a personalized user interfaces for a text mining e-Research tool called NaCTeM. eRaUI will be adaptable to different usages and different level of researchers’ knowledge and preferences increasing the use of NaCTeM e-research tools by making it easier to learn and adaptable to the requirements of different user groups.
Project Team: Prof. Farhi Marir, Dr. Sahithi Siva and Dr. Yanguo Jing

Wednesday, 12 October 2011

We discussed the implementation of two main WP2 functionalities of eRAUI: machine learning algorithms to model the behaviour of user and content-based algorithm to support the user in his search.

First of all, we saw Eamonn demonstration of the new DOM element-relative user behaviour tracking, which has been designed to greatly improve the accuracy of tracking versus the previous system which was page-relative. We viewed the action of eRaUI user behaviour tracking on the current NaCTeM feedback form, and saw how it is possible to track user keypresses. We discussed producing some new video demonstrations of the current functionality of eRaUI including a tour of the mechanism by which data is recorded into the eRaUI central database. These shall be available on the eRaUI blog shortly. Farhi asked Eamonn to consider the implementation of ontology of terms which would be used to match commonly searched-for keywords and the anchor text of links to levels of user expertise. Since the anchor text of links clicked on within NaCTeM are recorded automatically in the back-end database, these can be stored in a dictionary which an administrator can then classify according to expertise level. This will facilitate the classification of users, for instance, into novice, expert and PhD level.During the meeting,Eamonn was able to prototype and demonstrate the workability of this feature. Farhi suggested that the user's level of expertise is not explicitly alterable from within the interface of the eRaUI widget - instead a system of internal classification - viz. that of the ontology mentioned above - shall be used instead.

We also discussed the use of window panes with eRaUI in order to present information which the user might be looking for in a cascading window format. The precise form this will take is yet to be established.

Eamonn suggested collaboration between E-research admin and individual users. We also decided that we shall give a presentation of the current functionality of eRaUI to the faculty of computing at London Metropolitan University on the 2nd November 2011. Further to this, we have got some of our MSc students involved in the project with the CPP103N Software Engineering module (Large Scale OODB Development). These students are currently working upon aspects of eRaUI from a software engineering context.